"AI aggregators are a subset of wrappers - they're startups that aggregate multiple LLMs into one interface or API layer to route queries across models and give users access to multiple models. These companies typically provide an orchestration layer that includes monitoring, governance, or eval tooling. Think: AI search startup Perplexity or developer platform OpenRouter, which provides access to multiple AI models via a single API."
""LLM wrappers are essentially startups that wrap existing large language models, like Claude, GPT, or Gemini, with a product or UX layer to solve a specific problem. An example would be a startup that uses AI to helps students study. "If you're really just counting on the back end model to do all the work and you're almost white-labeling that model, the industry doesn't have a lot of patience for that anymore," Mowry said on this week's episode of Equity.""
Startups that simply wrap existing large language models with a product or UX layer and minimal proprietary IP are encountering skepticism and dwindling investor patience. Thinly differentiated LLM wrappers no longer gain traction by white-labeling backend models; sustainable startups must build deep, wide moats through horizontal differentiation or domain-specific vertical advantages. Successful examples include coding and legal assistants with stronger moats. AI aggregators combine multiple LLMs into a single interface or API, offering orchestration features like monitoring, governance, and evaluation tooling, and provide unified access to multiple models for users and developers.
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